Continental Cumulus Research Articles

Combining observations and simulations to investigate the small-scale variability of surface solar irradiance under continental cumulus clouds

Abstract. The amount of solar radiation reaching the Earth surface (surface solar irradiance, SSI) is critical for a variety of applications, ranging from surface–atmosphere interactions to solar energy. SSI is characterized by a large spatiotemporal variability, in particular in the presence of cumulus clouds. This results in complex spatial patterns of shadows and sunlight directly related to clouds' geometry and physical properties. Although key in many respects, the instantaneous spatial distribution of SSI remains largely unexplored. Here, we use unique observations from a dense network of pyranometers deployed during the HOPE field campaign to investigate the SSI spatial distribution. For cumulus scenes, bimodal distributions are found, with one mode corresponding to cloud shadows and the other to sunlit areas with enhanced SSI exceeding clear-sky values. Combining large-eddy simulations of cumulus clouds with Monte Carlo ray tracing, we demonstrate the capability of advanced numerical tools to reproduce the observed distributions and quantify the impact of cloud geometrical and physical properties on both modes. In particular, cloud cover strongly modulates their amplitudes, in addition to their position and width, which are also sensitive to cloud height, geometrical depth, and liquid water content. Combining observations and simulations, we also explore sampling strategies to estimate the SSI spatial distribution with a limited number of sensors, suggesting that 10 pyranometers integrated over 10 min can capture most details of the full distribution. Such a strategy could be used for future campaigns to further investigate SSI distributions and their impact on land–atmosphere exchanges or photovoltaic farm management.

Microphysical structure and vertical evolution of continental cumulus clouds from analysis of aircraft measurements in Northern China

Microphysical characteristics of continental cumulus in relatively remote area of Northern China were studied using King Air aircraft that equipping with several cloud probes in summer of 2020. Penetrating of cumuli was achieved at several altitudes. Aircraft based KPR cloud radar showed the depth of cumulus was over 4000 m and the cloud base was near 2000 m above sea level. Cloud droplet number concentration was 400–800 cm−3 at 3700–4300 m and decreased to 200 cm−3 at the cloud top. Cloud droplet effective diameter increased linearly with height (3.33 μm km−1) from 12 μm (3700 m) to 18 μm (5500 m), as the result of droplet growth by condensation or accretion, during the vertical evolution of cloud from initial generation to mature stage. Cloud droplet size spectra presented a single mode at all altitudes and the broadening of spectra with increasing altitude was apparent. LWC adiabatic ratios of <0.3 for all altitudes indicated the strong entrainment mixing from dry air, since most of the clouds were penetrated near cloud margins. At 4300 m, drizzle drop concentration reached 17 L−1 (diameter of 60 μm) and high concentration of ice (175 L−1, diameter gathered at 150 μm and over 1000 μm) containing primarily graupels was related to the secondary ice process during riming (Hallett–Mossop). Supercooled drizzle drops (60, 100 and 150 μm in diameter) and ice particles (100–400 μm in diameter) both had concentrations of several counts per liter at 5500 m. At the convective cloud top (6200 m), high concentrations of drizzle drops and ice particles (mainly graupels) revealed their large growth rates as atmospheric condition was more fit for the redistribution and collision/coalescence of cloud particles. To better learn the large differences of cloud properties and related microphysics for distinct levels of well-developed continental cumulus, more aircraft measurements, particularly across the cloud cores, are needed.

Vertical Distributions of Aerosol and Cloud Microphysical Properties and the Aerosol Impact on a Continental Cumulus Cloud Based on Aircraft Measurements From the Loess Plateau of China

Based on aircraft measurements of aerosols and continental cumulus clouds made over the Loess Plateau of China (Xinzhou, Shanxi Province) on 30 July 2020, this study focuses on the vertical profiles of microphysical properties of aerosols and cumulus clouds, and use them to study aerosol-cloud interactions. During the study period, the boundary layer was stable with a height ∼1,500 m above sea level. Aerosols in the boundary layer mainly came from local emissions, while aerosols above this layer were mostly dust aerosols transported over long distances. Vertical profiles of aerosols and cloud condensation nuclei were obtained, and aerosol activation ratios at different supersaturation (SS) levels ranged from 0.16 to 0.32 at 0.2% SS and 0.70 to 0.85 at 0.8% SS. A thick cumulus cloud in the development stage was observed from the bottom to the top with the horizontal dimension of 10 km by 7 km, the cloud-base height of 2,450 m (15.8°C), and the cloud-top height of 5,400 m (−3°C). The maximum updraft velocity near the cloud top was 13.45 m s−1, and the maximum downdraft velocity occuring in the upper-middle part of the cloud was 4.44 ms−1. The temperature inside the cloud was higher than the outside, with their difference being positively correlated with the cloud water content. The temperature lapse rate inside the cloud was about −6.5°C km−1. The liquid water content and droplet effective radius (Re) increased with increasing height. The cloud droplet number concentration (Nc) increased first then decreased, peaking in the middle and lower part of the cloud, the average values of Nc and Re were 767.9 cm−3 and 5.17 μm, respectively. The cloud droplet spectrum had a multi-peak distribution, with the first appearing at ∼4.5 μm. SS in the cloud first increased then decreased with height. The maximum SS is ∼0.7% appearing at ∼3,800 m. The conversion rate of intra-cloud aerosols to cloud droplets was between 0.2 and 0.54, with the ratio increasing gradually with increasing height. The cloud droplet spectral dispersion and Nc were positively correlated. The aerosol indirect effect (AIE) was estimated to be 0.245 and 0.16, based on Nc and Re, respectively. The cloud droplet dispersion mainly attenuated the AIE, up to ∼34.7%.

Identification of polluted clouds and composition analysis based on GF-5 DPC data

Large amounts of fine polluted particles due to anthropogenic activities can enter into the lower atmosphere and may pollute the lower water clouds, especially continental cumulus. Continental polluted cumulus (CPCU) plays an important role in the process of atmospheric radiative transfer and the Earth's environmental change. Based on the sensitivity of polarization to small particles, GF-5 DPC data were used to identify polluted clouds. In addition, dynamic transport and composition of polluted clouds were further analyzed. Firstly, a novel method based on two tests was used to identify polluted clouds in China. The source and transport characteristics of the polluted clouds were analyzed by using wind field and backward trajectory pattern. Secondly, based on the monitoring data from the Sun‐sky radiometer Observation NETwork (SONET), the types of atmospheric aerosol composition in China were classified into ten types by considering influences of the climate types, Digital Elevation Model and social economy, etc. Finally, the composition of polluted clouds in different regions was further identified according to regional aerosol composition, and the results were verified by the Optical Properties of Aerosols and Clouds (OPAC) software.The identifying results of polluted clouds showed that there were four polluted clouds over China on May 27, 2018 and high concentration of small dust particles. The changes in the component ratios of different polluted clouds respond well to the results of airflow sources and transport. Compared with the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Vertical Feature Mask (VFM) data, the proposed method is effective and robust. The proposed method of identification and composition analysis based on GF-5 DPC data for polluted clouds can enrich the application of DPC data in the field of atmospheric and environmental detection.

Quantification of the Radiative Effect of Aerosol–Cloud Interactions in Shallow Continental Cumulus Clouds

Abstract The indirect radiative effect of aerosol variability on shallow cumulus clouds is realized in nature with considerable concurrent meteorological variability. Large-eddy simulations constrained by observations at a continental site in Oklahoma are performed to represent the variability of different meteorological states on days with different aerosol conditions. The total radiative effect of this natural covariation between aerosol and other meteorological drivers of total cloud amount and albedo is quantified. The changes to these bulk quantities are used to understand the response of the cloud radiative effect to aerosol–cloud interactions (ACI) in the context of concurrent processes, as opposed to attempting to untangle the effect of individual processes on a case-by-case basis. Mutual information (MI) analysis suggests that meteorological variability masks the strength of the relationship between cloud drop number concentration and the cloud radiative effect. This is shown to be mostly due to variation in solar zenith angle and cloud field horizontal heterogeneity masking the relationship between cloud drop number and cloud albedo. By combining MI and more traditional differential analyses, a framework to identify important modes of covariation between aerosol, clouds, and meteorological conditions is developed. This shows that accounting for solar zenith angle variation and implementing an albedo bias correction increases the detectability of the radiative effects of ACI in simulations of shallow cumulus.

Theoretical Understanding of the Linear Relationship between Convective Updrafts and Cloud-Base Height for Shallow Cumulus Clouds. Part II: Continental Conditions

Abstracts This is the Part II of a two-part study that seeks a theoretical understanding of an empirical relationship for shallow cumulus clouds: subcloud updraft velocity covaries linearly with the cloud-base height. This work focuses on continental cumulus clouds that are more strongly forced by surface fluxes and more deviated from equilibrium than those over oceans (Part I). We use a simple analytical model for shallow cumulus that is well tested against a high-resolution (25 m in the horizontal) large-eddy simulation model. Consistent with a conventional idea, we find that surface Bowen ratio is the key variable that regulates the covariability of both parameters: under the same solar insolation, a drier surface allows for stronger buoyancy flux, triggering stronger convection that deepens the subcloud layer. We find that the slope of the Bowen-ratio-regulated relationship between the two parameters (defined as λ) is dependent on both the local time and the stability of the lower free atmosphere. The value of λ decreases with time exponentially from sunrise to early afternoon and linearly from early afternoon to sunset. The value of λ is larger in a more stable atmosphere. In addition, continental λ in the early afternoon more than doubles the oceanic λ. Validation of the theoretical results against ground observations over the Southern Great Plains shows a reasonable agreement. Physical mechanisms underlying the findings are explained from the perspective of different time scales at which updrafts and cloud-base height respond to a surface flux forcing.

Momentum Transport in Shallow Cumulus Clouds and Its Parameterization by Higher‐Order Closure

AbstractIt is challenging to parameterize subgrid vertical momentum fluxes in marine shallow cumulus layers that contain a jet in the profile of horizontal wind. In a large‐eddy simulation of such a layer, it is found that the momentum flux in the direction of strongest wind magnitude has a three‐layer structure. The lowest layer, from the ocean surface up to the jet maximum, has downgradient momentum flux. The middle layer, from the jet maximum up to an altitude several hundred meters above, has upgradient (i.e., countergradient) momentum flux because of transport of low‐magnitude momentum upward through the jet maximum. In the upper layer, the layer‐average momentum flux is weak. The budget of momentum flux shows that in the middle and upper layers, both the buoyancy production term and turbulent advection (i.e., third‐order flux‐of‐flux) terms are important.To parameterize the profile of momentum flux in a single‐column model, the momentum flux is prognosed in this study. The buoyancy production and flux‐of‐flux terms are parameterized by integrating them over a subgrid probability density function with an assumed normal‐mixture shape. The resulting parameterized fluxes and mean‐wind profiles are demonstrated to be comparable to those produced in large‐eddy simulations, both for two marine shallow cumulus cases with upgradient fluxes and for a continental cumulus case and two stratocumulus cases with downgradient fluxes. In the two marine shallow cumulus cases, the parameterization is able to capture the upgradient momentum flux above the jet maximum and the weak momentum fluxes aloft.

Theoretical Understanding of the Linear Relationship between Convective Updrafts and Cloud-Base Height for Shallow Cumulus Clouds. Part I: Maritime Conditions

Abstract Zheng and Rosenfeld found linear relationships between the convective updrafts and cloud-base height zb using ground-based observations over both land and ocean. The empirical relationships allow for a novel satellite remote sensing technique of inferring the cloud-base updrafts and cloud condensation nuclei concentration, both of which are important for understanding aerosol–cloud–climate interactions but have been notoriously difficult to retrieve from space. In Part I of a two-part study, a theoretical framework is established for understanding this empirical relationship over the ocean. Part II deals with continental cumulus clouds. Using the bulk concept of mixed-layer (ML) model for shallow cumulus, I found that this relationship arises from the conservation law of energetics that requires the radiative flux divergence of an ML to balance surface buoyancy flux. Given a certain ML radiative cooling rate per unit mass Q, a deeper ML (higher zb) undergoes more radiative cooling and requires stronger surface buoyancy flux to balance it, leading to stronger updrafts. The rate with which the updrafts vary with zb is modulated by Q. The cooling rate Q manifests strong resilience to external large-scale forcing that spans a wide range of climatology, allowing the slope of the updrafts–zb relationship to remain nearly invariant. This causes the relationship to manifest linearity. The physical mechanism underlying the resilience of Q to large-scale forcing, such as free-tropospheric moisture and sea surface temperature, is investigated through the lens of the radiative transfer theory (two-stream Schwarzschild equations) and an ML model for shallow cumulus.

Power-Law Scaling in the Internal Variability of Cumulus Cloud Size Distributions due to Subsampling and Spatial Organization

AbstractIn this study, the spatial structure of cumulus cloud populations is investigated using three-dimensional snapshots from large-domain LES experiments. The aim is to understand and quantify the internal variability in cloud size distributions due to subsampling effects and spatial organization. A set of idealized shallow cumulus cases is selected with varying degrees of spatial organization, including a slowly organizing marine precipitating case and five more quickly organizing diurnal cases over land. A subdomain analysis is applied, yielding cloud number distributions at sample sizes ranging from severely undersampled to nearly complete. A strong power-law scaling is found in the relation between cloud number variability and subdomain size, reflecting an inverse linear relation. Scaling subdomain size by cloud size yields a data collapse across time points and cases, highlighting the role played by cloud spacing in controlling the stochastic variability. Spatial organization acts on top of this baseline model by increasing the maximum cloud size and by enhancing the variability in the number of smallest clouds. This reflects that the smaller clouds start to live on top of larger-scale thermodynamic structures, such as cold pools, which favor or inhibit their formation. Compositing all continental cumulus cases suggests the existence of a prototype diurnal time dependence in the spatial organization. A simple stochastic expression for cloud number variability is proposed that is formulated in terms of two dimensionless groups, which allows objective estimation of the degree of spatial organization in simulated and observed cumulus cloud populations.

The summer diurnal cycle of coastal cloudiness over west Iberia using Meteosat/SEVIRI and a WRF regional climate model simulation

The summer time cloud diurnal cycle over western Iberia is analysed here using a satellite climate data record of fractional cloud cover based on 9 years of Meteosat Second Generation observations which is distributed by the EUMETSAT's Climate Monitoring Satellite Applications Facility. These observations were complemented with a corresponding mean cloud diurnal cycle using SYNOP reports on six locations over the studied domain. It is shown that the main coastal mountain range separates regions that are characterized by two very different cloud regimes: stratocumulus-topped boundary layer convection dominates the region towards the coast and continental cumulus convection dominates the region to the east of these mountains. To explain the observed variability, a long-term regional climate model [Weather Research and Forecasting model (WRF)] simulation over Iberia was used. A comparison of the observations against model output for the common period between observations and simulation shows that although the model generally underestimates cloudiness, it is able to represent the diurnal cycle in a realistic manner. It is shown that the observed cloud diurnal evolution is linked to the thermal circulations generated by the land-sea contrast and orography. The extent to which the cloud deck penetrates inland is closely related to the coastal orography: although smaller hills tend to enhance cloudiness, larger mountains block the progression of the marine boundary layer further inland, as it behaves as a density current. Larger mountains also produce katabatic flow and a rather strong subsidence aloft during the night. The warming due to this subsidence helps the blocking of the cloud deck as it is partially responsible for evaporating clouds, as shown by a potential temperature budget analysis.

Insights from modeling and observational evaluation of a precipitating continental cumulus event observed during the MC3E field campaign

AbstractA case of shallow cumulus and precipitating cumulus congestus sampled at the Atmospheric Radiation Measurement Program Southern Great Plains supersite during the Midlatitude Continental Convective Clouds Experiment is analyzed using a multisensor observational approach and numerical simulation. Observations from a new radar suite surrounding the facility are used to characterize the evolving statistical behavior of the precipitating cloud system. This is accomplished using distributions of different measures of cloud geometry and precipitation properties. Large‐eddy simulation (LES) with size‐resolved (bin) microphysics is employed to determine the forcings most important in producing the salient aspects of the cloud system captured in the radar observations. Our emphasis is on assessing the importance of time‐varying versus steady state large‐scale forcing on the model's ability to reproduce the evolutionary behavior of the cloud system. Additional consideration is given to how the characteristic spatial scale and homogeneity of the forcing imposed on the simulation influences the evolution of cloud system properties. Results indicate that several new scanning radar estimates such as distributions of cloud top are useful to differentiate the value of time‐varying (or at least temporally well‐matched) forcing on LES solution fidelity.

Ground-Based Remote Retrievals of Cumulus Entrainment Rates

Abstract While fractional entrainment rates for cumulus clouds have typically been derived from airborne observations, this limits the size and scope of available datasets. To increase the number of continental cumulus entrainment rate observations available for study, an algorithm for retrieving them from ground-based remote sensing observations has been developed. This algorithm, called the Entrainment Rate In Cumulus Algorithm (ERICA), uses the suite of instruments at the Southern Great Plains (SGP) site of the U.S. Department of Energy's Atmospheric Radiation Measurement Program (ARM) Climate Research Facility as inputs into a Gauss–Newton optimal estimation scheme, in which an assumed guess of the entrainment rate is iteratively adjusted through intercomparison of modeled cloud attributes to their observed counterparts. The forward model in this algorithm is the explicit mixing parcel model (EMPM), a cloud parcel model that treats entrainment as a series of discrete entrainment events. A quantified value for the uncertainty in the retrieved entrainment rate is also returned as part of the retrieval. Sensitivity testing and information content analysis demonstrate the robust nature of this method for retrieving accurate observations of the entrainment rate without the drawbacks of airborne sampling. Results from a test of ERICA on 3 months of shallow cumulus cloud events show significant variability of the entrainment rate of clouds in a single day and from one day to the next. The mean value of 1.06 km−1 for the entrainment rate in this dataset corresponds well with prior observations and simulations of the entrainment rate in cumulus clouds.

A simplified PDF parameterization of subgrid‐scale clouds and turbulence for cloud‐resolving models

Over the past decade a new type of global climate model (GCM) has emerged, which is known as a multiscale modeling framework (MMF). Colorado State University's MMF represents a coupling between the Community Atmosphere Model and the System for Atmospheric Modeling (SAM) to serve as the cloud‐resolving model (CRM) that replaces traditionally parameterized convection in GCMs. However, due to the high computational expense of the MMF, the grid size of the embedded CRM is typically limited to 4 km for long‐term climate simulations. With grid sizes this coarse, shallow convective processes and turbulence cannot be resolved and must still be parameterized within the context of the embedded CRM. This paper describes a computationally efficient closure that aims to better represent turbulence and shallow convective processes in coarse‐grid CRMs. The closure is based on the assumed probability density function (PDF) technique to serve as the subgrid‐scale (SGS) condensation scheme and turbulence closure that employs a diagnostic method to determine the needed input moments. This paper describes the scheme, as well as the formulation of the eddy length which is empirically determined from large eddy simulation (LES) data. CRM tests utilizing the closure yields good results when compared to LESs for two trade‐wind cumulus cases, a transition from stratocumulus to cumulus, and continental cumulus. This new closure improves the representation of clouds through the use of SGS condensation scheme and turbulence due to better representation of the buoyancy flux and dissipation rates. In addition, the scheme reduces the sensitivity of CRM simulations to horizontal grid spacing. The improvement when compared to the standard low‐order closure configuration of the SAM is especially striking.

Aerosol effect on droplet spectral dispersion in warm continental cumuli

In situ aircraft measurements of cloud microphysical properties and aerosol during the 1st phase of the Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX‐I) over the Indian sub‐continent provided initial opportunities to investigate the dispersion effect and its implications for estimating aerosol indirect effects in continental cumuli. In contrast to earlier studies on continental shallow cumuli, it is found that not only the cloud droplet number concentration but also the relative dispersion increases with the aerosol number concentration in continental cumuli. The first aerosol indirect effect estimated from the relative changes in droplet concentration and effective radius with aerosol number concentration are 0.13 and 0.07, respectively. In‐depth analysis reveals that the dispersion effect could offset the cooling by enhanced droplet concentration by 39% in these continental cumuli. Adiabaticity analysis revealed aerosol indirect effect is lesser in subadiabatic clouds possibly due to inhomogeneous mixing processes. This study shows that adequate representation of the dispersion effect would help in accurately estimating the cloud albedo effect for continental cumuli and can reduce uncertainty in aerosol indirect effect estimates.

Evaluating Boundary Layer–Based Mass Flux Closures Using Cloud-Resolving Model Simulations of Deep Convection

AbstractHigh-resolution three-dimensional cloud resolving model simulations of deep cumulus convection under a wide range of large-scale forcings are used to evaluate a mass flux closure based on boundary layer convective inhibition (CIN) that has previously been applied in parameterizations of shallow cumulus convection. With minor modifications, it is also found to perform well for deep oceanic and continental cumulus convection, and it matches simulated cloud-base mass flux much better than a closure based only on the boundary layer convective velocity scale. CIN closure maintains an important feedback among cumulus base mass flux, compensating subsidence, and CIN that keeps the boundary layer top close to cloud base. For deep convection, the proposed CIN closure requires prediction of a boundary layer mean turbulent kinetic energy (TKE) and a horizontal moisture variance, both of which are strongly correlated with precipitation. For our cases, CIN closure predicts cloud-base mass flux in deep convective environments as well as the best possible bulk entraining CAPE closure, but unlike the latter, CIN closure also works well for shallow cumulus convection without retuning of parameters.

Very Early Formation of Big, Liquid Drops Revealed by ZDR in Continental Cumulus

Abstract Examination of the early radar echo histories of several vigorous, cumulus clouds in northeast Colorado and northwest Kansas, with sensitive, dual-polarization radar, reveals the formation of millimeter-sized water drops at about the same time that the conventional, first precipitation echo (from ice) forms aloft. The early, positive ZDR values appear in the vicinity of the 0°C level (the radar data do not specify height accurately) and soon extend both above and below it. Positive ZDR is found within and to the upwind side of the updraft, separate from the conventional first precipitation echoes, which appear first at higher altitude, generally downwind of the updraft core, and have no significantly positive ZDR. Big, liquid drops were not expected this early in the formation of continental cumulus. The early presence of supercooled water drops larger than cloud droplets may be a significant factor in the glaciation of these clouds. The kind of early radar coverage illustrated here would be a priceless adjunct to aircraft studies of precipitation formation in cumulus. Microphysical data from aircraft must be interpreted with numerical models in order to deduce (or verify) the processes, and such models require the kind of early data illustrated here, both for initialization and verification.

Effect of aerosol on warm convective clouds: Aerosol‐cloud‐surface flux feedbacks in a new coupled large eddy model

We present a new large eddy simulation model that comprises coupled components representing size‐resolved aerosol and cloud microphysics, radiative properties of aerosol and clouds, dynamics, and a surface soil and vegetation model. The model is used to investigate the effect of increases in aerosol on liquid water path LWP, cloud fraction, optical depth, and precipitation formation in warm, continental cumulus clouds. Sets of simulations that either neglect, or include the radiative properties of a partially absorbing aerosol are performed. In the absence of aerosol radiative effects, an increase in aerosol loading results in a reduction in precipitation. However, the clouds do not experience significant changes in LWP, cloud fraction and cloud depth; aerosol effects on LWP and cloud fraction are small compared to the dynamical variability of the clouds at any given aerosol concentration. Reasons for this response are discussed. When aerosol radiative effects are included, the modification in atmospheric heating profiles, and the reduction in surface latent and sensible heat fluxes resulting from the presence of these particles, have a significant effect on cloud parameters and boundary layer evolution. For the case considered, there is a significant reduction in the strength of convection, LWP, cloud fraction and cloud depth. Cloud optical depth responds non‐monotonically to the increase in aerosol. These results indicate that in continental regions surface processes must be included in calculations of aerosol‐cloud‐precipitation interactions. Neglect of these surface processes may result in an overestimate of the second aerosol indirect effect.

Similarity of Deep Continental Cumulus Convection as Revealed by a Three-Dimensional Cloud-Resolving Model

A three-dimensional cloud-resolving simulation of midlatitude continental convection during the Atmospheric Radiation Measurement (ARM) program summer 1997 intensive observation period (IOP) is used to study the similarity of several second and third statistical moments, and second-moment budgets among five episodes of deep convection. Several parameter scales relevant to deep convection similarity are introduced. The dimensionless vertical profiles of the vertical velocity variance and its third moment, cumulus kinetic energy, the prognostic variables' variances and fluxes, their budgets, as well as several triple correlations cluster together, confirming the dynamical similarity of the simulated convective events. The dimensionless budgets of several second-order moments, such as convective kinetic energy (CKE), its vertical and horizontal components, variance, and vertical fluxes of the prognostic thermodynamic variables, as well as the momentum flux, are also presented. The most interesting aspect of the simulated CKE budget is that, in contrast to the boundary layer and shallow trade wind cumulus convection, the dissipation term is relatively small compared to the dominant buoyancy production, transport, and pressure correlation terms. The prognostic equation for the bulk CKE, defined as the vertically integrated mean CKE per unit area, is also discussed. It is found that the so-called bulk CKE dissipation timescale ranges in the simulation from 4 to 8 h. Therefore, the bulk CKE, mostly contained in the horizontal branches of mesoscale circulations associated with the deep convective systems, can persist much longer than the lifetime of an individual convective cloud. It is also found that the fraction of the bulk CKE associated with the vertical motions is about the same for all of the events considered, suggesting a strong correlation between the bulk CKE and the strength of the convective updrafts. It is shown that the bulk CKE dissipation timescale is inversely proportional to the square root of the bulk CKE itself. It is also found that the convective velocity scale is closely related to the convective available potential energy (CAPE) of the thermodynamic sounding taken immediately before a particular convective event.

An intercomparison of cloud‐resolving models with the atmospheric radiation measurement summer 1997 intensive observation period data

AbstractThis paper reports an intercomparison study of midlatitude continental cumulus convection simulated by eight two‐dimensional and two three‐dimensional cloud‐resolving models (CRMs), driven by observed large‐scale advective temperature and moisture tendencies, surface turbulent fluxes, and radiative‐heating profiles during three sub‐periods of the summer 1997 Intensive Observation Period of the US Department of Energy's Atmospheric Radiation Measurement (ARM) program. Each sub‐period includes two or three precipitation events of various intensities over a span of 4 or 5 days. The results can be summarized as follows.CRMs can reasonably simulate midlatitude continental summer convection observed at the ARM Cloud and Radiation Testbed site in terms of the intensity of convective activity, and the temperature and specific‐humidity evolution. Delayed occurrences of the initial precipitation events are a common feature for all three sub‐cases among the models. Cloud mass fluxes, condensate mixing ratios and hydrometeor fractions produced by all CRMs are similar. Some of the simulated cloud properties such as cloud liquid‐water path and hydrometeor fraction are rather similar to available observations. All CRMs produce large downdraught mass fluxes with magnitudes similar to those of updraughts, in contrast to CRM results for tropical convection. Some inter‐model differences in cloud properties are likely to be related to those in the parametrizations of microphysical processes.There is generally a good agreement between the CRMs and observations with CRMs being significantly better than single‐column models (SCMs), suggesting that current results are suitable for use in improving parametrizations in SCMs. However, improvements can still be made in the CRM simulations; these include the proper initialization of the CRMs and a more proper method of diagnosing cloud boundaries in model outputs for comparison with satellite and radar cloud observations. Copyright © 2002 Royal Meteorological Society

Updraft and Downdraft Statistics of Simulated Tropical and Midlatitude Cumulus Convection

Abstract This paper presents a detailed analysis of updraft and downdraft statistics of simulated tropical oceanic and midlatitude continental cumulus convection, with an emphasis on the individual terms in the vertical momentum budget. Strong convective cores with absolute vertical velocities over 1 m s−1 and total condensate mixing ratios over 0.1 g kg−1 are sampled from several long-term simulations, driven by the observed large-scale advective forcings over the eastern Atlantic and Oklahoma regions. The median updraft and downdraft velocities are weakly dependent upon height, but the 90th percentile of the updraft velocity varies strongly with height, with a maximum in the middle troposphere. The median updraft thermal buoyancies are only about 0.5 K higher than those of downdrafts. As in aircraft measurements, positive thermal buoyancies exist for more than half of downdraft cores, and negative thermal buoyancies exist for a significant number of updrafts. The existence of the nonhydrostatic pressure...